Yudai Sadakuni

Papers

Total Citations

H-Index

About

Yudai Sadakuni is a robotics researcher specializing in autonomous navigation systems, with a focus on integrating geometric and semantic environmental understanding. His work centers on developing navigation frameworks that enable robots to perceive and traverse complex outdoor environments without relying on expensive, high-fidelity maps. In his highly cited 2017 paper, Sadakuni introduced an autonomous navigation system that constructs a 3D map containing both geometric features—such as curbs, walls, and street trees—and semantic labels for sidewalks, roadways, and crosswalks. This dual-layered map allows robots to reason about their surroundings more intelligently, distinguishing drivable areas from obstacles. His 2018 follow-up work advanced the field further by demonstrating robust road-following navigation using a simplified Edge-Node Graph derived from electronic maps. This approach reduces computational overhead while maintaining reliable localization and environmental recognition. Collectively, his papers have garnered over 20 citations, reflecting their practical impact on autonomous vehicle and mobile robot research. Sadakuni’s contributions are particularly notable for bridging the gap between detailed 3D mapping and lightweight, real-world deployable navigation systems.